Ship pipeline series washing method and system based on digital twinning

Abstract

According to the ship pipeline series washing method and system based on digital twinning, virtual simulation and actual testing are combined, parameters such as the actual oil temperature, the filter stage number, the pump and the valve are set and corrected in real time according to data of a virtual simulation model, meanwhile, the concentration parameters of all branch pipeline systems tested in a test are monitored in real time, and the real-time monitoring of the pipeline system concentration parameters is achieved. The virtual simulation model is continuously corrected, the pipeline cleaning state is continuously predicted, unnecessary series washing time is avoided, and the ship pipeline series washing efficiency is improved. And finally, the oil flow system virtual simulation model is utilized to evaluate the oil intermingling period with the oil intermingling cleanliness requirement meeting the grade requirement, and the time consumed by the ship oil flow system intermingling is estimated. According to the technical scheme, efficient evaluation is carried out on the whole pipeline series washing cycle, the time needed by series washing is estimated, and the human input of series washing is reduced.

Description

Technical Field

[0001] The present application relates to the field of ship design technology, and in particular, to a ship pipeline serial washing method and system based on digital twins. Background Art

[0002] As the "blood vessels" of ships, pipelines are responsible for the flow and heat exchange of water, oil, steam, gas and other media within and between ship systems. Before the pipeline system is officially put into operation, a crucial step is the series cleaning process to ensure that the cleanliness of the pipeline meets the design requirements, especially for the oil flow system, whose high viscosity and strict cleaning standards make the series cleaning process particularly complex and time-consuming.

[0003] At present, the domestic shipbuilding industry faces a series of challenges in the cross-washing of oil flow systems. Due to the lack of clear and quantifiable cross-washing control standards, shipyards often rely on accumulated experience when setting the cross-washing time, which not only increases the subjectivity of the operation, but also easily leads to unstable cross-washing effects. Sometimes there will be excessive cleaning, resulting in a waste of resources; sometimes there may be insufficient cleaning, leaving pollution risks and affecting the long-term stable operation of the system.

[0004] The diversity of ship designs and the complexity of oil flow systems make the formulation of series washing plans particularly difficult. The oil flow characteristics of different ship types and different systems are different, requiring targeted series washing strategies. However, the current industry lacks a unified basis for judgment and standardized operating procedures, resulting in significant differences in actual operations among different engineering personnel, making it difficult to effectively control the series washing cycle. In addition, the uncontrollability of the series washing cycle of the oil flow system has a profound impact on the entire ship construction cycle. Due to the extension of the series washing cycle, the arrangement of subsequent processes is seriously disturbed, and the resource allocation plan for personnel, consumables, etc. is disrupted, increasing the difficulty and cost of project management. At the same time, the long series washing process also leads to the consumption of a large amount of fuel and the increase of man-hours, further increasing the cost of ship construction.

[0005] In summary, the series washing process of the ship's oil pipeline system has become one of the bottlenecks restricting the ship construction cycle and quality. It is urgent to achieve precise control and optimization of the series washing process. Summary of the invention

[0006] The purpose of this application is to provide a ship pipeline serial washing method and system based on digital twins to solve the problem of low serial washing efficiency of the current ship pipeline system.

[0007] In order to achieve the above objectives, this application adopts the following technical solutions:

[0008] A ship pipeline washing method based on digital twins includes: obtaining the pollution level of pollutants in the ship pipeline system, and if the pollutant pollution level is greater than or equal to the target level, judging that the ship pipeline system needs to be washed; constructing a first attenuation simulation model based on the first relevant parameter of the ship pipeline system, the first attenuation model is used to estimate the washing cycle of the current ship pipeline system, and if the estimated washing cycle is less than the target washing cycle, washing the current ship pipeline system; the first attenuation simulation model is expressed by the following formula:

[0009]

[0010] Where: c represents the pollutant concentration in the ship's piping system, C 12 represents the initial pollution concentration in the ship's piping system, q represents the oil flow rate, and β represents the filtration ratio of the filter;

[0011] Obtain the first real-time pollutant pollution level measured during the current ship pipeline system series washing process, construct a second attenuation simulation model, use the second attenuation model to output the simulated second real-time pollutant pollution level, and compare the second real-time pollutant pollution level with the first real-time pollutant pollution level; the second attenuation simulation model is the same as the first attenuation simulation model or is the first attenuation simulation model after optimizing the parameters; if the comparison result meets the virtual-real error requirement, continue to perform series washing on the ship pipeline system until the series washing is completed.

[0012] In some embodiments, the method further includes: obtaining the Reynolds number of the oil flow in the ship piping system, and comparing the Reynolds number of the oil flow with a critical Reynolds number; if the Reynolds number of the oil flow is greater than or equal to the critical Reynolds number, performing a series wash on the ship piping system; if the Reynolds number of the oil flow is less than the critical Reynolds number, adjusting the parameters related to the pipe diameter, pump or external pipe set in the ship piping system; the calculation of the Reynolds number is expressed as follows:

[0013]

[0014] Wherein, Re represents the Reynolds number, u represents the flow velocity in the pipe, v represents the kinematic viscosity, and d represents the inner diameter of the pipe at the corresponding position; the critical Reynolds number is 4000.

[0015] In some embodiments, if the estimated series washing cycle is greater than the target series washing cycle, the parameters related to the pipe diameter, pump or external pipe set in the ship pipeline system are adjusted until the estimated series washing cycle is less than the target series washing cycle.

[0016] In some embodiments, when the ship's pipeline system is washed, the real-time pollutant concentration in each branch is obtained, and the estimated washing cycle required to reach the corresponding pollution level is calculated, and the estimated washing cycle is compared with the target washing cycle. If the comparison result is less than a threshold value, the washing continues.

[0017] In some embodiments, if the comparison result is greater than a threshold, a three-dimensional model of the local pipeline structure is constructed, a three-dimensional flow field simulation is carried out, and the flow field information of the three-dimensional space in the local pipeline is obtained, the flow structure in the local pipeline is screened, and the accessory parameters of the local pipeline are optimized. This optimization method at least includes measures such as pipe diameter optimization, pump performance optimization, and external pipeline optimization in the pipeline series washing system. The optimization adjustment may include single-objective optimization, such as optimizing the Reynolds number of the oil flow in the pipeline; it may also include multi-objective optimization, such as optimizing the Reynolds number of the oil flow in the pipeline while also meeting the critical velocity of the oil flow in each branch.

[0018] In some embodiments, if the comparison result between the second real-time pollutant pollution level and the first real-time pollutant pollution level does not meet the virtual-real error requirement, the flow oil temperature, filter stage, pump parameters and valve parameters in the ship pipeline system are adjusted to optimize the second attenuation simulation model.

[0019] The second aspect of the present application provides a ship pipeline washing system based on digital twins, including a pollution level test module, a washing cycle estimation module, a virtual-real comparison module and an execution module, wherein the pollution level test module is used to obtain the pollution level of pollutants in the ship pipeline system. If the pollutant pollution level is greater than or equal to the target level, it is judged that the ship pipeline system needs to be washed; the washing cycle estimation module is used to construct a first attenuation simulation model based on the first relevant parameter of the ship pipeline system, and the first attenuation simulation model is used to estimate the washing cycle of the current ship pipeline system. If the estimated washing cycle is less than the target washing cycle, the current ship pipeline system is washed; the first attenuation simulation model is expressed by the following formula:

[0020]

[0021] Where: c represents the pollutant concentration in the ship's piping system, c 12represents the initial pollution concentration in the ship's pipeline system, q represents the oil flow rate, and β represents the filtration ratio of the filter; the virtual-real comparison module is used to obtain the first real-time pollutant pollution level measured during the current ship's pipeline system washing process, and to construct a second attenuation simulation model, and to use the second attenuation model to output the simulated second real-time pollutant pollution level, and to compare the second real-time pollutant pollution level with the first real-time pollutant pollution level; the second attenuation simulation model is the same as the first attenuation simulation model or is the first attenuation simulation model after optimizing the parameters; the execution module is used to execute subsequent steps according to the comparison result. If the comparison result meets the virtual-real error requirement, the ship's pipeline system continues to be washed until the washing is completed.

[0022] In some embodiments, an information interaction module is also included, which is used to input the measured data of the ship pipeline system during the actual series washing process into the series washing cycle estimation module and the virtual-real comparison module, and output the simulation data of the series washing cycle estimation module and the virtual-real comparison module to the actual ship pipeline system for adjustment.

[0023] A third aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program runs on a processor, the processor executes the method described in the first aspect.

[0024] The fourth aspect of the present application provides an electronic device, comprising: at least one memory for storing programs; and at least one processor for executing the programs stored in the memory. When the programs stored in the memory are executed, the processor is used to execute the method described in the first aspect.

[0025] Compared with the prior art, the present invention has the following advantages:

[0026] The present application provides a ship pipeline series washing method and system based on digital twins, which combines virtual simulation with actual testing, sets and corrects parameters such as actual oil temperature, filter level, pump, valve, etc. with data from the virtual simulation model, and monitors the concentration parameters of each branch pipe system tested in real time, continuously corrects the virtual simulation model, and continuously predicts the pipeline cleanliness status, avoiding unnecessary series washing time, and improving the efficiency of ship pipeline series washing. Finally, the oil flow system virtual simulation model is used to evaluate the series oil cycle that meets the grade requirements for oil cleanliness, and the time consumed by the ship oil flow system series washing is estimated. The technical solution of the present application efficiently evaluates the entire cycle of pipeline series washing, estimates the time required for series washing, and reduces the manpower input for series washing. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 A schematic diagram of a process of a ship pipeline serial washing method based on digital twins according to an embodiment of the present application is shown;

[0029] Figure 2 A schematic diagram of a process of a ship pipeline serial washing method based on digital twins according to another embodiment of the present application is shown;

[0030] Figure 3 A schematic diagram of the structure of a one-dimensional group of a ship piping system is shown;

[0031] Figure 4 It shows the structural schematic diagram of the control equipment installed in each branch of the ship's piping system;

[0032] Figure 5 It shows the schematic diagram of the structure of the test equipment installed on each branch of the ship's piping system;

[0033] Figure 6 The diagram shows the pollutant concentration decay curve and the schematic diagram of the washing stage during the washing of the ship's pipeline system;

[0034] Figure 7 A schematic diagram showing the three-dimensional flow field simulation at a local location in a ship piping system. DETAILED DESCRIPTION

[0035] The technical solutions of the specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings. These implementation methods are only used to illustrate the present application, but not to limit the present application.

[0036] The term "and / or" in this application is a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. In the present invention, the symbol " / " indicates that the associated objects are in an "or" relationship, for example, "A / B" means "A or B".

[0037] The terms "first" and "second" in the specification and claims of this application are used to distinguish different objects rather than to describe a specific order of the objects. For example, "first response message" and "second response message" are used to distinguish different response messages rather than to describe a specific order of the response messages.

[0038] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be considered as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0039] In the description of the embodiments of the present application, unless otherwise specified, "multiple" means two or more than two. For example, multiple processing units refer to two or more processing units, etc., and multiple elements refer to two or more elements, etc.

[0040] A ship pipeline serial washing method and system based on digital twin of the present application is described in detail below with reference to the accompanying drawings.

[0041] Figure 1 The figure shows a flow chart of a method for serial washing of ship pipelines based on digital twins according to an embodiment of the present application. Figure 1 As shown, the ship pipeline serial washing method based on digital twin in the embodiment of the present application includes the following steps:

[0042] The pollutant pollution level of the ship pipeline system is obtained. If the pollutant pollution level is greater than the target level, it is judged that the ship pipeline system needs to be washed in series. The real-time pollutant concentration data of each washing branch after the initial circulation of the ship pipeline is obtained by online measuring equipment. The initial circulation can be understood as the circulation without adding filters and filter elements in the ship pipeline to determine the initial level of the oil flow. If the pollutant concentration is greater than the target level, it is judged that the ship pipeline system needs to be washed in series. In one embodiment, the pollution level can be judged according to the proportion of the number of pollutant particle sizes in the ship pipeline system (i.e., the concentration of pollutants). The degree of pollution is characterized by the NAS standard, and the real-time NAS (National Aerospace Standard 1638, National Aerospace Standard 1638) standard level data of each branch of the ship pipeline system is obtained by online measuring equipment. For example, a monitor that can measure the size and number of particles in real time can be selected, or a sensor that monitors multiple parameters at the same time, such as particle concentration, particle size distribution, etc., can be selected, and these data can be converted into NAS levels through algorithms or software.

[0043] Furthermore, the aforementioned target level can be determined according to the specific usage scenario of the ship pipeline system. For example, the target level can be set to level 8. If the pollution level of pollutants in the ship pipeline system is less than or equal to the target level, it means that the oil flow quality of the ship pipeline system has met the requirements, and the ship pipeline system has ended the series washing or does not need series washing. If the pollution level of pollutants in a branch of the ship pipeline system is greater than the target level, it indicates that the ship pipeline system needs to be washed. It can be understood that the target level of the aforementioned ship pipeline system is only exemplary and not restrictive. When designing the target level, those skilled in the art can design it specifically according to the different uses of the oil flow medium.

[0044] A first attenuation simulation model is constructed based on the first relevant parameter of the ship's pipeline system, and the first attenuation simulation model is used to estimate the wash cycle of the ship's pipeline system. If the estimated wash cycle is less than the target wash cycle, the current ship's pipeline system is washed. If the estimated wash cycle is greater than the target wash cycle, the parameters related to the pipe diameter, pump or external pipe set in the ship's pipeline system are adjusted until the estimated wash cycle is less than the target wash cycle. The aforementioned first attenuation simulation model can be expressed by the following formula:

[0045]

[0046] Where: c represents the pollutant concentration in the ship's piping system, c 12 It represents the initial pollution concentration in the ship's piping system, q represents the oil flow rate, and β represents the filtration ratio of the filter.

[0047] In one embodiment, the aforementioned ship pipeline series washing method based on digital twins may also include: obtaining the Reynolds number of the oil flow in the ship pipeline system, comparing the Reynolds number of the oil flow with the critical Reynolds number, and if the Reynolds number of the oil flow is greater than or equal to the critical Reynolds number, the ship pipeline system is series washed. If the Reynolds number of the oil flow is less than the critical Reynolds number, the parameters related to the pipeline, pump or external pipeline set in the ship pipeline system are adjusted, and the first attenuation simulation model after optimization is obtained accordingly.

[0048] In one embodiment, the present application uses one-dimensional pipe network simulation software such as Applied Flow Technology, Flomaster and other commercial software or self-written pipe network software to perform one-dimensional configuration solution. Figure 3As shown in the figure, by building a pipeline flow model in the overall ship pipeline system to drive a one-dimensional simulation system, the dynamic change data of parameters such as flow and pressure in the pipeline are obtained. At the same time, the flow resistance parameters of the valve at different openings are combined, and the valve opening, pump parameters and other settings in the system are obtained according to the obtained pipeline flow model, pump and valve accessory inlet and outlet parameters, initial concentration of pollutants and online measurement implementation detection data. Combined with the temperature, flow velocity, flow rate and pressure data measured in the ship pipeline system operation experiment, correction guidance is provided for obtaining high-precision flow characteristic parameters of the system pipeline.

[0049] Based on the temperature-viscosity curve of the flowing oil, combined with the experimental measurement temperature obtained above, the kinematic viscosity of the flowing oil can be calculated. Combined with the flow velocity of the flowing oil in the pipe, the Reynolds number is calculated by the following formula.

[0050]

[0051] Where: Re is the Reynolds number, [-]; u is the flow velocity in the pipe, [m / s]; v is the kinematic viscosity, [CST]; d is the inner diameter of the pipe at the corresponding position, [m].

[0052] In a specific embodiment, the aforementioned critical Reynolds number can be set to 4000. When the flow oil Reynolds number of each branch of the ship's pipeline system is greater than or equal to 4000, it indicates that the flow of each branch is in a turbulent state, and the pipeline can be quickly washed. If the flow oil Reynolds number of each branch is less than 4000, it means that there are branches that have not reached a turbulent state and the washing effect is poor, then the relevant parameters are further adjusted until each branch flow is in a turbulent state. The adjusted related parameters can be single-target and multi-target. For example, the adjustment parameters only meet the flow state, which is a single target. Multi-target adjustment can be to meet both the flow state and the critical velocity of the flowing medium in the pipeline. It can also be understood that the present application can be characterized by a critical velocity that can simultaneously evaluate the transport state of pollutant particles and the flowing medium. The present application is only illustrated by the Reynolds number.

[0053] like Figure 4As shown, the ship piping system may also include various installed equipment. In a specific embodiment, if the Reynolds number of each branch is greater than the critical Reynolds number, and the estimated series washing cycle is less than the target series washing cycle, the oil temperature, filter level, pump, valve and other parameters in the actual ship piping system can be set according to the parameters corresponding to the above conditions through information interaction, and combined with real-time monitoring of pollutant concentration data. It is also possible to install an oscillator in each branch to clearly plan the accuracy ladder configuration of each level of filter elements according to different series washing stages and filter element dirty blockage conditions. At the same time, according to the equipment settings and periodic evaluation results, the planning of conditional guarantee measures such as manual arrangement and auxiliary equipment arrangement can be carried out. In order to ensure the normal operation of the equipment, the setting status can be checked, and the inspection items can include static state inspection and operation inspection of equipment such as pressure instruments, temperature instruments and online measuring devices at the beginning of operation.

[0054] Figure 5 A structural schematic diagram of a ship piping system is shown. During the actual series washing, the pressure instruments, temperature instruments and online measuring devices of each branch in the ship piping system are turned on. During the process, the filter and the series washing circuit should be checked regularly for leakage. During the series washing process, the first real-time pollutant pollution level measured during the series washing process of the current ship piping system is obtained. The first real-time pollutant pollution level is obtained by real-time measurement and recording of the pollution degree data of each branch using an online measuring device. The pollutant concentration is determined. If the NAS of each branch is <8, it indicates that the oil flow quality meets the requirements and the series washing of the oil flow system is completed; if there is a branch NAS ≥ 8, the series washing continues.

[0055] Furthermore, the target wash cycle required to reach the target pollution level can be compared with the estimated wash cycle. When washing the ship's pipeline system, the real-time pollutant concentration in each branch is obtained, and the estimated wash cycle required to reach the corresponding pollution level is calculated. The target wash cycle is compared with the estimated wash cycle. If the comparison result is less than the threshold, the wash continues. The threshold setting can be 1 day.

[0056] When the comparison result is greater than the threshold, it indicates that there is a specific flow structure in the ship's pipeline system. Combined with the pipeline flow model, pump and valve accessory inlet and outlet parameters, initial pollutant concentration, and online measurement implementation detection data, a three-dimensional model of the local pipeline structure is established and mesh discretization is performed. Carry out three-flow flow field simulation and quickly obtain the flow field information of the full three-dimensional space in the pipeline. Using an efficient order reduction algorithm, real-time calculation of the three-dimensional flow field can be achieved in seconds. The process simulation results are obtained by interpolation method. Figure 7 As shown, the system ship piping system and accessory parameters are optimized for typical flow structures, the flow dead zones inside the corresponding pipelines and other flow structures that are not conducive to rapid washing are eliminated, and the optimization results of the pipeline and accessory parameters are recorded and fed back.

[0057] Furthermore, in the serial washing method of the embodiment of the present application, a second attenuation simulation model can be constructed, and the second attenuation simulation model is the same as the first attenuation simulation model or is the first attenuation simulation model after optimizing the parameters. Figure 6 As shown in the figure, the pollutant concentration attenuation curve is drawn based on the historical measured pollutant concentration attenuation data of the ship pipeline system. It can be seen from the pollutant concentration attenuation curve that the wash cycle can be divided into the efficient wash stage and the fluctuating wash stage. In the efficient wash stage, the white box algorithm is used for physical mechanism analysis, and the real-time pollutant concentration of each branch of the simulation is solved through the second attenuation simulation model. The NAS level of the ship pipeline system is determined in accordance with the standard GJB 420B-2006 to obtain the simulated second real-time pollutant pollution level. In the fluctuating wash stage, the pollutant concentration fluctuates randomly and the trend is difficult to control. The black box algorithm is used to solve the pollutant concentration of each branch through big data analysis.

[0058] Compare the aforementioned first real-time pollutant pollution level with the second real-time pollutant pollution level. If the comparison structure of the two meets the virtual-real error requirements, it indicates that the second attenuation simulation model can accurately evaluate the series washing cycle of the ship's pipeline system and can achieve efficient series washing. In order to further ensure the accuracy of the second attenuation simulation model, the real-time monitoring data in the ship's pipeline system can be input into the current second attenuation simulation model to achieve iterative updates. If the first real-time pollutant pollution level does not meet the virtual-real error requirements after comparison with the second real-time pollutant pollution level, the second attenuation simulation model or the first attenuation simulation model can be optimized by adjusting parameters such as oil temperature, filter level, pump, valve, etc. In a specific embodiment, the aforementioned virtual-real error can be, for example, 1 day. If the virtual-real error is less than or equal to 1 day, it indicates that the second attenuation simulation model can accurately evaluate the series washing cycle of the ship's pipeline system.

[0059] The second aspect of the present application provides a ship pipeline series washing system based on digital twins, including a pollution level test module, a series washing cycle estimation module, a virtual-real comparison module and an execution module. Among them, the pollution level test module is used to obtain the pollution level of pollutants in the ship pipeline system. If the pollution level of pollutants is greater than or equal to the target level, it is judged that the ship pipeline system needs to be series washed. The aforementioned target level can determine the corresponding level according to the specific usage scenario of the ship pipeline system. For example, the target level can be set to level 8. If the pollution level of pollutants in the ship pipeline system is less than or equal to the target level, it indicates that the oil flow quality of the ship pipeline system has met the requirements, and the ship pipeline system ends series washing or does not need series washing. If the pollution level of pollutants in a branch of the ship pipeline system is greater than the target level, it indicates that the ship pipeline system needs to be series washed.

[0060] The wash cycle estimation module is used to construct a first attenuation simulation model based on the first relevant parameters of the ship's pipeline system. The first attenuation simulation model is used to estimate the wash cycle of the current ship's pipeline system. If the estimated wash cycle is less than the target wash cycle, the current ship's pipeline system is washed; if the estimated wash cycle is greater than the target wash cycle, the parameters related to the pipe diameter, pump or external pipeline set in the ship's pipeline system are adjusted to obtain the optimized first attenuation simulation model, until the estimated wash cycle is less than the target wash cycle. The first attenuation simulation model is expressed by the following formula:

[0061]

[0062] Where: c represents the pollutant concentration in the ship's piping system, c 12 It represents the initial pollution concentration in the ship's piping system, q represents the oil flow rate, and β represents the filtration ratio of the filter.

[0063] The virtual-real comparison module is used to obtain the first real-time pollutant pollution level measured during the current ship pipeline system washing process, and to construct a second attenuation simulation model. The second attenuation model is used to output the simulated second real-time pollutant pollution level, and the second real-time pollutant pollution level is compared with the first real-time pollutant pollution level. The second attenuation simulation model is the same as the first attenuation simulation model or is the first attenuation simulation model after optimizing the parameters.

[0064] Compare the aforementioned first real-time pollutant pollution level with the second real-time pollutant pollution level. If the comparison structure of the two meets the virtual-real error requirement, it indicates that the second attenuation simulation model can accurately evaluate the series washing cycle of the ship's pipeline system and can achieve efficient series washing. In order to further ensure the accuracy of the second attenuation simulation model, the real-time monitoring data in the ship's pipeline system can be input into the current second attenuation simulation model to achieve iterative update. In a specific embodiment, the aforementioned virtual-real error can be, for example, 1 day. If the virtual-real error is less than or equal to 1 day, it indicates that the second attenuation simulation model can accurately evaluate the series washing cycle of the ship's pipeline system.

[0065] The execution module is used to execute subsequent steps according to the comparison result. If the comparison result meets the virtual-real error requirement, the ship pipeline system continues to be washed until the washing is completed. If the first real-time pollutant pollution level does not meet the virtual-real error requirement after comparison with the second real-time pollutant pollution level, the second attenuation simulation model or the first attenuation simulation model can be optimized by adjusting parameters such as oil temperature, filter level, pump, valve, etc. After optimization, the optimal second attenuation simulation model is obtained and the simulation data is re-output and compared with the measured data until the virtual-real error requirement is met.

[0066] In one embodiment, the aforementioned series washing system may also include an information interaction module, which is used to input the measured data of the ship piping system during the actual series washing process into the series washing cycle estimation module and the virtual-real comparison module, and output the simulation data of the series washing cycle estimation module and the virtual-real comparison module to the actual ship piping system for adjustment. The information interaction module refers to standards such as Information Technology Sensor Network (GB / T 30269.504-2019) to achieve port intercommunication, and uses information technology and sensor networks to combine experimental testing and virtual simulation modules to achieve real-time information interaction.

[0067] It should be understood that the specific process of each module executing the above corresponding steps has been described in detail in the above method embodiment, and for the sake of brevity, it will not be repeated here.

[0068] It should also be understood that the division of modules in the embodiments of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional module in each embodiment of the present application may be integrated into a processor, or may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0069] The third aspect of the present application provides a computer-readable storage medium, on which a program of a ship pipeline serial washing method based on digital twins is stored, so that the ship pipeline serial washing method based on digital twins provided in the first aspect of the present application is executed. As for the aforementioned computer-readable storage medium, those skilled in the art can understand that the implementation example of the functions of the above-mentioned system and each unit can be completed by hardware related to the computer program. The aforementioned computer program can be stored in a computer-readable storage medium. When the program is executed, it executes an implementation example including the functions of the above-mentioned system and each unit. The aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM or optical disk.

[0070] The fourth aspect of the present application provides an electronic device, comprising: at least one memory for storing programs; at least one processor for executing the programs stored in the memory. The electronic device may be a server. The electronic device comprises a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device comprises a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the electronic device is used to communicate with an external client via a network connection. When the computer program is executed by the processor, the functions or steps of the ship pipeline serial washing method based on digital twins of the present application are realized.

[0071] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present application. These improvements and substitutions should also be regarded as the scope of protection of the present application.

Claims

1. A ship pipeline serial washing method based on digital twin, characterized in that: include: Obtaining the pollution level of pollutants in the ship piping system, and if the pollution level of pollutants is greater than or equal to the target level, determining that the ship piping system needs to be washed; A first attenuation simulation model is constructed based on the first relevant parameter of the ship pipeline system. The first attenuation model is used to estimate the wash cycle of the current ship pipeline system. If the estimated wash cycle is less than the target wash cycle, the current ship pipeline system is washed. The first attenuation simulation model is expressed by the following formula: Where: c represents the pollutant concentration in the ship's piping system, c 12 represents the initial pollution concentration in the ship's piping system, q represents the oil flow rate, and β represents the filtration ratio of the filter; Based on the digital twin technology, a first real-time pollutant pollution level measured during the current ship pipeline system washing process is obtained, and a second attenuation simulation model is constructed, and a second real-time pollutant pollution level simulated by the second attenuation model is output, and the second real-time pollutant pollution level is compared with the first real-time pollutant pollution level; The second attenuation simulation model is the same as the first attenuation simulation model or is the first attenuation simulation model after parameter optimization; If the comparison result meets the virtual-real error requirement, the ship piping system continues to be washed until the washing is completed.

2. The digital twin-based ship pipeline serial washing method according to claim 1 is characterized in that: Also includes: Obtaining the Reynolds number of the oil flow in the ship's pipeline system, and comparing the Reynolds number of the oil flow with a critical Reynolds number; if the Reynolds number of the oil flow is greater than or equal to the critical Reynolds number, performing a series wash on the ship's pipeline system; if the Reynolds number of the oil flow is less than the critical Reynolds number, adjusting parameters related to pipe diameters, pumps or external pipes set in the ship's pipeline system; The calculation of the Reynolds number is expressed as follows: In the formula, Re represents the Reynolds number, u represents the flow velocity in the pipe, v represents the kinematic viscosity, and d represents the inner diameter of the pipe at the corresponding position; The critical Reynolds number is 4000.

3. The ship pipeline serial washing method based on digital twin according to claim 1 is characterized in that: If the estimated series washing cycle is greater than the target series washing cycle, the parameters related to the pipe diameter, pump or external pipe set in the ship pipeline system are adjusted until the estimated series washing cycle is less than the target series washing cycle.

4. The ship pipeline serial washing method based on digital twin according to claim 1 is characterized in that: When the ship pipeline system is washed in series, the real-time pollutant concentration in each branch is obtained, and the estimated washing cycle required to reach the corresponding pollution level is calculated. The estimated washing cycle is compared with the target washing cycle. If the comparison result is less than the threshold, the washing is continued.

5. The ship pipeline serial washing method based on digital twin according to claim 4 is characterized in that: If the comparison result is greater than the threshold, a three-dimensional model of the local pipeline structure is constructed, a three-dimensional flow field simulation is carried out, and the flow field information of the three-dimensional space in the local pipeline is obtained. The flow structure in the local pipeline is screened and the accessory parameters of the local pipeline are optimized.

6. The ship pipeline serial washing method based on digital twin according to claim 1 is characterized in that: If the comparison result between the second real-time pollutant pollution level and the first real-time pollutant pollution level does not meet the virtual-real error requirement, the flow oil temperature, filter stage, pump parameters and valve parameters in the ship pipeline system are adjusted to optimize the second attenuation simulation model.

7. A ship pipeline washing system based on digital twin, characterized in that: It includes pollution level test module, series washing cycle estimation module, virtual-real comparison module and execution module, among which, The pollution level test module is used to obtain the pollution level of pollutants in the ship's piping system. If the pollution level of pollutants is greater than or equal to the target level, it is determined that the ship's piping system needs to be washed; The cross-wash cycle estimation module is used to construct a first attenuation simulation model based on the first relevant parameter of the ship pipeline system. The first attenuation simulation model is used to estimate the cross-wash cycle of the current ship pipeline system. If the estimated cross-wash cycle is less than the target cross-wash cycle, the current ship pipeline system is cross-washed. The first attenuation simulation model is expressed by the following formula: Where: c represents the pollutant concentration in the ship's piping system, C 12 represents the initial pollution concentration in the ship's piping system, q represents the oil flow rate, and β represents the filtration ratio of the filter; The virtual-real comparison module is used to obtain the first real-time pollutant pollution level measured during the current ship pipeline system series washing process based on the digital twin technology, and to construct a second attenuation simulation model, and to use the second attenuation model to output the simulated second real-time pollutant pollution level, and to compare the second real-time pollutant pollution level with the first real-time pollutant pollution level; the second attenuation simulation model is the same as the first attenuation simulation model or is the first attenuation simulation model after optimizing the parameters; The execution module is used to execute subsequent steps according to the comparison result. If the comparison result meets the virtual-real error requirement, the ship pipeline system continues to be washed until the washing is completed.

8. A digital twin-based ship pipeline washing system according to claim 1, characterized in that: It also includes an information interaction module, which is used to input the measured data of the ship pipeline system during the actual series washing process into the series washing cycle estimation module and the virtual-real comparison module, and output the simulation data of the series washing cycle estimation module and the virtual-real comparison module to the actual ship pipeline system for adjustment.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed on a processor, the processor is caused to execute the method according to any one of claims 1 to 6.

10. An electronic device, characterized in that: include: at least one memory for storing a program; At least one processor is used to execute the program stored in the memory, and when the program stored in the memory is executed, the processor is used to execute the method according to any one of claims 1 to 6.

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